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What is the current overlap between computational neuroscience and GPU computing? Well, not that much. Definitely smaller than in fields such as bioinformatics. I suspect that since many simulation environments for the neuroscientist are already quite mature and complex it is hard to modify them to include CUDA functionality. The experience in our lab is that existing code running on the CPU cannot be simply transformed to the GPU. Considerable re-writing of the code is required and in many cases it is easier to start from scratch. Adding CUDA fun

In our research group based in Aarhus, Denmark, we're excited about the possibilities that gpucomputing.net and it's local communities bring for sharing experiences on GPU computing. We kick-off by giving a small presentation of what we do in our group and who is involved.

Greetings! I'd like to introduce myself to this community and look forward to posting and conversing with you all about algorithms and data structures on the GPU. This is an area that's particularly interesting to me as a researcher; algorithms and data structures have been the core of much of our group's research.

Recently tried my hand at the CUDA Superhero Challenge 2. Tried a quick-and-dirty brute-force attempt just to see if it was even remotely possible in the time constraints (it wasn't), and then did a little Monte Carlo exploration, which did much better. Still, the solutions I was getting in the time limit were scoring way below the standing leaders, and I ran out of ideas.